• Delivering analytical and characterisation excellence in nanomaterial risk assessment: a tiered approach

    Delivering analytical and characterisation excellence in nanomaterial risk assessment: a tiered approach

  • Introducing confidence, adaptability and clarity into nanomaterial risk assessment

    Introducing confidence, adaptability and clarity into nanomaterial risk assessment

  • Facilitating decision-making in choice of techniques and SOPs

    Facilitating decision-making in choice of techniques and SOPs

ACEnano in a nutshell

ACEnano will introduce confidence, adaptability and clarity into nanomaterial risk assessment by developing a widely implementable and robust tiered approach to nanomaterials physicochemical characterisation that will simplify and facilitate contextual (hazard or exposure) description and its transcription into a reliable nanomaterials grouping framework.

vision


This will be achieved by the creation of a “conceptual toolbox” including a tiered approach to cost efficient nanomaterials analysis that will facilitate decision-making in choice of techniques and SOPs, linked to a characterisation ontology framework for grouping and risk assessment.
ACEnano will initiate activities to support data collection, management, interpretation and delivery to a data warehouse for safe use & storage. It will thus underpin the future of nanomaterial quality control, labelling and anti-counterfeiting.

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Latest news

Invitation to a demo of the OpenRiskNet e-infrastructure

The e-infrastructure project OpenRiskNet developing a platform providing data and modelling tools for predictive toxicology and risk assessment and coordinated by DouglasConnect, is entering its second stage, in which the platform is made accessible to everyone. In the first phase, advanced concepts have been developed and implemented into the first version of the platform including building and deploying of virtual research environments (VREs), a reference environment accessible by everyone for testing, harmonized and partly semantically annotated data and modelling services, corresponding training material as well as seven risk assessment case studies, which are used to evaluate and optimize the infrastructure.

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